Computer Sciences Commons^™

Collocation Error Correction In Web Queries And Text Documents, Alan T. Varghese

Theses, Dissertations and Culminating Projects

Collocations are words in English that occur together frequently. Non-native speakers of English tend to confuse certain terms with other similar terms. This causes one of the terms to be substituted with a term that is not commonly used with the other term. “Powerful tea” is an example of such an odd collocation. In this scenario the more commonly used term is “strong tea”.

This paper proposes an approach called CollOrder to detect such odd collocations in written English. CollOrder also provides suggestions to correct the odd collocate. These suggestions are filtered and ranked as top-k suggestions.

We make use …

Integrating A Lighting System With Objective Light Movement, Kiel Pease

All Theses

When applying a light design within computer graphics software, there is no clear-cut way to achieve accurate and noticeable light movement without rigorous work animating the lighting tools by hand. This task can be arduous and involve constant test renders throughout a single frame range. This project strives to explain the production of a short animated feature, by incorporating a video-based lighting system, which is intended to assist with scenes that require objective light movement. The video-based lighting method will strive to minimize (not eliminate) the need to animate by hand light motion from environment lighting. Since lighting design is …

Exploration Of Mouth Shading And Lighting In Cg Production, Chaoren Li

All Theses

The lighting and shading of human teeth in current computer animation features and live-action movies with effects are often intentionally avoided or processed by simple methods since they interact with light in complex ways through their intricate layered structure. The semi-translucent appearance of natural human teeth which result from subsurface scattering is difficult to replicate in synthetic scenes, though two techniques are often implemented. The first technique is to create an anatomically correct layered model, and render the teeth with both theoretically and empirically derived optical parameters of human teeth using physical subsurface materials. The second technique largely takes advantage …

Teaching And Assessment Of Mathematical Principles For Software Correctness Using A Reasoning Concept Inventory, Svetlana Drachova-Strang

All Dissertations

As computing becomes ubiquitous, software correctness has a fundamental role in ensuring the safety and security of the systems we build. To design and develop software correctly according to their formal contracts, CS students, the future software practitioners, need to learn a critical set of skills that are necessary and sufficient for reasoning about software correctness.
This dissertation presents a systematic approach to both introducing these reasoning skills into the curriculum, and assessing how well the students have learned them. Specifically, it introduces a comprehensive Reasoning Concept Inventory (RCI) that captures the fine details of basic reasoning skills that are …

The Application Of Embodied Conversational Agents For Mentoring African American Stem Doctoral Students, Kinnis Gosha

All Dissertations

This dissertation presents the design, development and short-term evaluation of an embodied conversational agent designed to mentor human users. An embodied conversational agent (ECA) was created and programmed to mentor African American computer science majors on their decision to pursue graduate study in computing. Before constructing the ECA, previous research in the fields of embodied conversational agents, relational agents, mentorship, telementorship and successful mentoring programs and practices for African American graduate students were reviewed. A survey used to find areas of interest of the sample population. Experts were then interviewed to collect information on those areas of interest and a …

Blogging Developer Knowledge: Motivations, Challenges, And Future Directions, Chris Parnin, Christoph Treude, Margaret-Anne Storey

Research Collection School Of Computing and Information Systems

Why do software developers place so much effort into writing public blog posts about their knowledge, experiences, and opinions on software development? What are the benefits, problems, and tools needed-what can the research community do to help? In this paper, we describe a research agenda aimed at understanding the motivations and issues of software development blogging. We interviewed developers as well as mined and analyzed their blog posts. For this initial study, we selected developers from various backgrounds: IDE plugin development, mobile development, and web development. We found that developers used blogging for a variety of functions such as documentation, …

An Architecture For Online Semantic Labeling On Ugvs, Arne Suppe, Luis Navarro-Serment, Daniel Munoz, Drew Bagnell, Martial Hebert

Research Collection School Of Computing and Information Systems

We describe an architecture to provide online semantic labeling capabilities to field robots operating in urban environments. At the core of our system is the stacked hierarchical classifier developed by Munoz et al.,1 which classifies regions in monocular color images using models derived from hand labeled training data. The classifier is trained to identify buildings, several kinds of hard surfaces, grass, trees, and sky. When taking this algorithm into the real world, practical concerns with difficult and varying lighting conditions require careful control of the imaging process. First, camera exposure is controlled by software, examining all of the image’s pixels, …

Unified Entity Search In Social Media Community, Ting Yao, Yuan Liu, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

The search for entities is the most common search behavior on the Web, especially in social media communities where entities (such as images, videos, people, locations, and tags) are highly heterogeneous and correlated. While previous research usually deals with these social media entities separately, we are investigating in this paper a unified, multilevel, and correlative entity graph to represent the unstructured social media data, through which various applications (e.g., friend suggestion, personalized image search, image tagging, etc.) can be realized more effectively in one single framework. We regard the social media objects equally as “entities” and all of these applications …

Fragmented Social Media: A Look Into Selective Exposure To Political News, Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

The hypothesis of selective exposure assumes that people crave like-minded information and eschew information that conflicts with their beliefs, and that has negative consequences on political life. Yet, despite decades of research, this hypothesis remains theoretically promising but empirically difficult to test. We look into news articles shared on Facebook and examine whether selective exposure exists or not in social media. We find a concrete evidence for a tendency that users predominantly share like-minded news articles and avoid conflicting ones, and partisans are more likely to do that. Building tools to counter partisanship on social media would require the ability …

Why Individuals Seek Diverse Opinions (Or Why They Don't), Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

Fact checking has been hard enough to do in traditional settings, but, as news consumption is moving on the Internet and sources multiply, it is almost unmanageable. To solve this problem, researchers have created applications that expose people to diverse opinions and, as a result, expose them to balanced information. The wisdom of this solution is, however, placed in doubt by this paper. Survey responses of 60 individuals in the UK and South Korea and in-depth structured interviews of 10 respondents suggest that exposure to diverse opinions would not always work. That is partly because not all individuals equally value …

Demand Forecasting Using A Growth Model And Negative Binomial Regression Framework, Cally Yeru Ong, Murphy Choy, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In this paper, we look at demand forecasting by using a growth model and negative binomial regression framework. Using cumulative sales, we model the sales data for different wristwatch brands and relate it to their sales and growth characteristics. We apply clustering to determine the distinctive characteristics of each individual cluster. Four different growth models are applied to the clusters to find the most suitable growth model to be used. After determining the appropriate growth model to be applied, we then forecast the sales by applying the model to new products being launched in the market and continue to monitor …

R-Energy For Evaluating Robustness Of Dynamic Networks, Ming Gao, Ee Peng Lim, David Lo

Research Collection School Of Computing and Information Systems

The robustness of a network is determined by how well its vertices are connected to one another so as to keep the network strong and sustainable. As the network evolves its robustness changes and may reveal events as well as periodic trend patterns that affect the interactions among users in the network. In this paper, we develop R-energy as a new measure of network robustness based on the spectral analysis of normalized Laplacian matrix. R-energy can cope with disconnected networks, and is efficient to compute with a time complexity of O (jV j + jEj) where V and E are …

Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe

Research Collection School Of Computing and Information Systems

This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …

Tag Recommendation In Software Information Sites, Xin Xia, David Lo, Xinyu Wang, Bo Zhou

Research Collection School Of Computing and Information Systems

Nowadays, software engineers use a variety of online media to search and become informed of new and interesting technologies, and to learn from and help one another. We refer to these kinds of online media which help software engineers improve their performance in software development, maintenance and test processes as software information sites. It is common to see tags in software information sites and many sites allow users to tag various objects with their own words. Users increasingly use tags to describe the most important features of their posted contents or projects. In this paper, we propose TagCombine, an automatic …

A Mapreduce Algorithm For Finding Hotspots Of Topics From Time Stamped Documents, Ashwathy Ashokan

Student Work

Hotspots of a word/topic are time periods with a burst of activities in a time stamped document set. Identifying and analyzing hot spots of topics has been an important area of research. Finding hot spots of topics requires processing of contents of documents which is often time consuming. In this thesis, we explore MapReduce style algorithms for computing hot spots of topics. MapReduce is a distributed parallel programming model and an associated implementation for processing and analyzing large datasets. User specifies a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce …

Unit-Level Isolation And Testing Of Buggy Code, Sanik Bajracharya

Student Work

In real-world software development, maintenance plays a major role and developers spend 50-80% of their time in maintenance-related activities. During software maintenance, a significant amount of effort is spent on ending and fixing bugs. In some cases, the fix does not completely eliminate the buggy behavior; though it addresses the reported problem, it fails to account for conditions that could lead to similar failures. There could be many possible reasons: the conditions may have been overlooked or difficult to reproduce, e.g., when the components that invoke the code or the underlying components it interacts with can not put it in …

3d Object Tracking And Motion Profiling, Corey A. Spitzer

Student Work

In order to advance the field of computer vision in the direction of “strong AI”, it’s necessary to address the subproblems of creating a system that can “see” in a way comparable to a human or animal. Due to very recent advances in depth-sensing imaging technology, it is now possible to generate accurate and detailed depth maps that can be used for image segmentation, mapping, and other higher-level processing functions needed for these subproblems. Using this technology, I describe a method for identifying a moving object in video and segmenting the image of the object based on its motion. This …

Traditional Media Seen From Social Media, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research Collection School Of Computing and Information Systems

With the advent of social media services, media outlets have started reaching audiences on social-networking sites. On Twitter, users actively follow a wide set of media sources, form interpersonal networks, and propagate interesting stories to their peers. These media subscription and interaction patterns, which had previously been hidden behind media corporations' databases, offer new opportunities to understand media supply and demand on a large scale. Through a map that connects 77 media outlets based on Twitter subscription patterns, we are able to answer a variety of questions: to what extent New York Times and the Wall Street Journal readers overlap? …

Tower Of Babel: A Crowdsourcing Game Building Sentiment Lexicons For Resource-Scarce Languages, Yoonsung Hong, Haewoon Kwak, Youngmin Baek, Sue. Moon

Research Collection School Of Computing and Information Systems

With the growing amount of textual data produced by online social media today, the demands for sentiment analysis are also rapidly increasing; and, this is true for worldwide. However, non-English languages often lack sentiment lexicons, a core resource in performing sentiment analysis. Our solution, Tower of Babel (ToB), is a language-independent sentiment-lexicon-generating crowdsourcing game. We conducted an experiment with 135 participants to explore the difference between our solution and a conventional manual annotation method. We evaluated ToB in terms of effectiveness, efficiency, and satisfactions. Based on the result of the evaluation, we conclude that sentiment classification via ToB is accurate, …

Analyzing The Friendliness Of Exchanges In An Online Software Developer Community, Brendan Cleary, Margaret-Anne Storey, Carlos Gómez, Leif Singer, Christoph Treude

Research Collection School Of Computing and Information Systems

Many online communities struggle with conflicts — e.g. between newcomers and elders — at some point. In July 2012, the Stack Exchange organization attempted to assess the overall “niceness” of the Stack Overflow community by rating the “friendliness” of 7,000 comments made on the site over a 4 year period. We performed a deeper examination of the comment dataset published by Stack Exchange. We find a high degree of comment repetition in the Stack Overflow database and suggest some simple heuristics that may help in automatically identifying unfriendly comments, providing managers of developer communities with simple means that could counter …

Onespace: Shared Depth-Corrected Video Interaction, David Ledo, Bon Adriel Aseniero, Sebastian Boring, Anthony Tang

Research Collection School Of Computing and Information Systems

Video conferencing commonly employs a video portal metaphor to connect individuals from remote spaces. In this work, we explore an alternate metaphor, a shared depth mirror, where video images of two spaces are merged into a single shared, depth-corrected video. Just as seeing one’s mirror image causes reflective interaction, the shared video space changes the nature of interaction in the video space. We realize this metaphor in OneSpace, where the space respects virtual spatial relationships between people and objects, and in so doing, encourages cross-site, full-body interactions. We report preliminary observations of OneSpace in use, describing the role of depth …

Vehicle Localization Along A Previously Driven Route Using An Image Database, Hideyuki Kume, Arne Suppe, Arne Suppe

Research Collection School Of Computing and Information Systems

In most autonomous driving applications, such as parking and commuting, a vehicle follows a previously taken route, or almost the same route. In this paper, we propose a method to localize a vehicle along a previously driven route using images. The proposed method consists of two stages: offline creation of a database, and online localization. In the offline stage, a database is created from images that are captured when the vehicle drives a route for the first time. The database consists of images, 3D positions of feature points estimated by structure-from-motion, and a topological graph. In the online stage, the …

Cost-Sensitive Double Updating Online Learning And Its Application To Online Anomaly Detection, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Although both cost-sensitive classification and online learning have been well studied separately in data mining and machine learning, there was very few comprehensive study of cost-sensitive online classification in literature. In this paper, we formally investigate this problem by directly optimizing cost-sensitive measures for an online classification task. As the first comprehensive study, we propose the Cost-Sensitive Double Updating Online Learning (CSDUOL) algorithms, which explores a recent double updating technique to tackle the online optimization task of cost-sensitive classification by maximizing the weighted sum or minimizing the weighted misclassification cost. We theoretically analyze the cost-sensitive measure bounds of the proposed …

Mining Sql Injection And Cross Site Scripting Vulnerabilities Using Hybrid Program Analysis, Lwin Khin Shar, Hee Beng Kuan Tan, Lionel C. Briand

Research Collection School Of Computing and Information Systems

In previous work, we proposed a set of static attributes that characterize input validation and input sanitization code patterns. We showed that some of the proposed static attributes are significant predictors of SQL injection and cross site scripting vulnerabilities. Static attributes have the advantage of reflecting general properties of a program. Yet, dynamic attributes collected from execution traces may reflect more specific code characteristics that are complementary to static attributes. Hence, to improve our initial work, in this paper, we propose the use of dynamic attributes to complement static attributes in vulnerability prediction. Furthermore, since existing work relies on supervised …

Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou

Research Collection School Of Computing and Information Systems

Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in Sina Weibo. Multimedia …

A Secure And Fair Resource Sharing Model For Community Clouds, Santhosh S. Anand

Graduate Theses and Dissertations

Cloud computing has gained a lot of importance and has been one of the most discussed segment of today's IT industry. As enterprises explore the idea of using clouds, concerns have emerged related to cloud security and standardization. This thesis explores whether the Community Cloud Deployment Model can provide solutions to some of the concerns associated with cloud computing. A secure framework based on trust negotiations for resource sharing within the community is developed as a means to provide standardization and security while building trust during resource sharing within the community. Additionally, a model for fair sharing of resources is …

Productivity In The Cognitive Overload Era, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Could technologies that emphasize the concept of "we" rather than "me" help modern society overcome its information overload?

The Chain-Link Fence Model: A Framework For Creating Security Procedures, Robert F. Houghton

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Information technology security professionals are facing an ever growing threat to the networks that they defend. The process for creating procedures to help stem this threat is very difficult for security professionals. The Chain-Link Fence Model helps security professionals by guiding them through the process of creating and implementing new security procedures.

Automated Midline Shift Detection On Brain Ct Images For Computer-Aided Clinical Decision Support, Xuguang Qi

Theses and Dissertations

Midline shift (MLS), the amount of displacement of the brain’s midline from its normal symmetric position due to illness or injury, is an important index for clinicians to assess the severity of traumatic brain injury (TBI). In this dissertation, an automated computer-aided midline shift estimation system is proposed. First, a CT slice selection algorithm (SSA) is designed to automatically select a subset of appropriate CT slices from a large number of raw images for MLS detection. Next, ideal midline detection is implemented based on skull bone anatomical features and global rotation assumptions. For the actual midline detection algorithm, a window …

Fans: Face Annotation By Searching Large-Scale Web Facial Images, Steven Hoi, Dayong Wang, I Yeu Cheng, Elmer Lin, Jianke Zhu, Ying He, Chunyan Miao

Research Collection School Of Computing and Information Systems

Auto face annotation is an important technique for many real-world applications, such as online photo album management, new video summarization, and so on. It aims to automatically detect human faces from a photo image and further name the faces with the corresponding human names. Recently, mining web facial images on the internet has emerged as a promising paradigm towards auto face annotation. In this paper, we present a demonstration system of search-based face annotation: FANS - Face ANnotation by Searching large-scale web facial images. Given a query facial image for annotation, we first retrieve a short list of the most …